Open AccessData Smoothing Numerical Methods and Their Applications in Unsupervised Learning for Prediction of Diabetes in Patients
Author(s) -
Satish Kumar Soni,
Ramjeevan Singh Thakur,
Anil Kumar Gupta
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i8196.078919
Subject(s) - smoothing , unsupervised learning , machine learning , computer science , diabetes mellitus , artificial intelligence , rest (music) , medicine , endocrinology , computer vision
Machine Learning in its fullest can provide much more accurate and enhanced analysis for medical diagnosis. In this paper we are trying to portray how the data related to diabetes can be used to predict if a person has diabetes or not. In more specific way this paper will explore the utilization of numerical methods smoothing with unsupervised learning to predict the early signs of disease like diabetes and rest.